Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, USA.
Massachusetts General Hospital and Harvard Medical School, Department of Radiation Oncology, Division of Radiation Biophysics, 100 Blossom St, Boston, MA 02114, USA.
Med Image Anal. 2024 Oct;97:103271. doi: 10.1016/j.media.2024.103271. Epub 2024 Jul 17.
Diffusion tensor imaging (DTI) is used in tumor growth models to provide information on the infiltration pathways of tumor cells into the surrounding brain tissue. When a patient-specific DTI is not available, a template image such as a DTI atlas can be transformed to the patient anatomy using image registration. This study investigates a model, the invariance under coordinate transform (ICT), that transforms diffusion tensors from a template image to the patient image, based on the principle that the tumor growth process can be mapped, at any point in time, between the images using the same transformation function that we use to map the anatomy. The ICT model allows the mapping of tumor cell densities and tumor fronts (as iso-levels of tumor cell density) from the template image to the patient image for inclusion in radiotherapy treatment planning. The proposed approach transforms the diffusion tensors to simulate tumor growth in locally deformed anatomy and outputs the tumor cell density distribution over time. The ICT model is validated in a cohort of ten brain tumor patients. Comparative analysis with the tumor cell density in the original template image shows that the ICT model accurately simulates tumor cell densities in the deformed image space. By creating radiotherapy target volumes as tumor fronts, this study provides a framework for more personalized radiotherapy treatment planning, without the use of additional imaging.
弥散张量成像（DTI）用于肿瘤生长模型，以提供肿瘤细胞浸润到周围脑组织的渗透途径的信息。当没有患者特异性 DTI 时，可以使用图像配准将模板图像（例如 DTI 图谱）转换为患者解剖结构。本研究基于肿瘤生长过程可以在图像之间使用相同的转换函数进行映射的原理，研究了一种从模板图像到患者图像转换扩散张量的模型，即坐标变换不变性（ICT）。ICT 模型允许从模板图像到患者图像映射肿瘤细胞密度和肿瘤前缘（作为肿瘤细胞密度的等水平），以便纳入放射治疗计划。所提出的方法转换扩散张量以模拟局部变形解剖中的肿瘤生长，并输出随时间推移的肿瘤细胞密度分布。该 ICT 模型在十名脑肿瘤患者的队列中进行了验证。与原始模板图像中的肿瘤细胞密度的比较分析表明，ICT 模型准确地模拟了变形图像空间中的肿瘤细胞密度。通过创建作为肿瘤前缘的放射治疗靶区，本研究提供了一种无需额外成像即可实现更个性化放射治疗计划的框架。
